Embedding Space Augmentation Some methods [1]}, [2]} augment the embedding space directly to obtain useful synthetic samples. Yin et al. [1]} assume that all classes follow a Gaussian distribution and translate samples from different classes about their means to generate new ones. Embedding expansion (EE) [2]} is a linear interpolation-based method to generate synthetic samples and mine for hard negatives by considering the pair-wise distances between real and synthetic points of different classes. It exhibits a trade-off between the quality of hard negatives and the computational load of calculating the pair-wise distances.
